Bayesian Prediction of Anxiety Level in Aged People at Rest Using 2-Channel NIRS Data from Prefrontal Cortex

  • Yukikatsu Fukuda
  • Wakana Ishikawa
  • Ryuhei Kanayama
  • Takashi Matsumoto
  • Naohiro Takemura
  • Kaoru Sakatani
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 812)

Abstract

The aim of this study was to predict mental stress levels of aged people at rest from two-channel near-infrared spectroscopy (NIRS) data from the prefrontal cortex (PFC). We used the State-Trait Anxiety Inventory (STAI) for the mental stress index.

We previously constructed a machine learning algorithm to predict mental stress level using two-channel NIRS data from the PFC in 19 subjects aged 20–24 years at rest (Sato et al., Adv Exp Med Biol 765:251–256, 2013). In the present study, we attempted the same prediction for aged subjects aged 61–79 years (10 women; 7 men). The mental stress index was again STAI. After subjects answered the STAI questionnaire, the NIRS device measured oxy- and deoxy-hemoglobin concentration changes during a 3-min resting state. The algorithm was formulated within a Bayesian machine learning framework and implemented by Markov Chain Monte Carlo. Leave-one-subject-out cross-validation was performed.

Average prediction error between the actual and predicted STAI values was 5.27. Prediction errors of 12 subjects were lower than 5.0. Since the STAI score ranged from 20 to 80, the algorithm appeared functional for aged subjects also.

Keywords

Anxiety Near infrared spectroscopy Prefrontal cortex Bayesian regression Aging 

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Copyright information

© Springer Science+Business Media, LLC 2014

Authors and Affiliations

  • Yukikatsu Fukuda
    • 1
  • Wakana Ishikawa
    • 1
  • Ryuhei Kanayama
    • 1
  • Takashi Matsumoto
    • 1
  • Naohiro Takemura
    • 2
  • Kaoru Sakatani
    • 3
  1. 1.Department of Electrical Engineering and BioscienceWaseda UniversityShinjuku-ku, TokyoJapan
  2. 2.Laboratory of Integrative Biomedical Engineering, Department of Electrical and Electronics Engineering, College of EngineeringNihon UniversityKoriyamaJapan
  3. 3.Department of Electrical and Electronics EngineeringNihon UniversityTokyoJapan

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